A database installation and deployment method based on MCP protocol

Abstract

The application discloses a database installation and deployment method based on an MCP protocol and relates to the technical field of database deployment.The scheme comprises the following steps: standardization configuration of private information is realized based on the MCP protocol, and a user completes relevant settings through an operation interface; with the aid of the natural language analysis capability of the MCP protocol, natural language deployment instructions input by the user are received, and a deployment process is triggered; an MCP Server calls MCP Tools to collect full environment information of a server, and a matching installation package version is obtained; the dependent conditions of a target environment are detected, and missing software packages are automatically supplemented; the database installation, initialization configuration and monitoring component deployment are automatically executed; and the MCP Server collects the state information of the above full process and returns a deployment result.The application can realize automatic and rapid installation and deployment of a database.

Description

Technical Field

[0001] This invention relates to the field of database deployment technology, specifically a database installation and deployment method based on the MCP protocol. Background Technology

[0002] I. Current Status of Technological Development

[0003] As enterprises deepen their digital transformation, databases, as the core infrastructure for data storage and processing, present significant challenges in terms of installation and deployment efficiency, reliability, and compatibility. Traditional database deployment processes rely on manual operation, requiring sequential steps such as environment testing, installation package matching, dependent software installation, parameter configuration, and cluster initialization. This involves multi-dimensional adaptation across server hardware architecture (x86 / ARM), operating systems (Linux / Windows / domestic operating systems), and network environments, resulting in high operational complexity and a high risk of errors. For distributed database clusters, manual configuration of node roles, data synchronization strategies, and failover mechanisms is also necessary, which is time-consuming, labor-intensive, and difficult to standardize, becoming a bottleneck in enterprise IT infrastructure construction.

[0004] II. Deficiencies and shortcomings of existing technologies

[0005] 1. Manual intervention is dominant, resulting in low deployment efficiency and a high barrier to entry. In traditional solutions, operations and maintenance personnel need to manually perform environment checks via command lines (such as using `lscpu` to check CPU architecture and `dpkg -l` to check dependent software) and select installation package versions based on experience. If dependent components (such as OpenSSL or Python runtime) are missing in the environment, matching versions must be manually found and compiled and installed. In this approach, single-node deployment takes an average of 4-6 hours, and cluster deployment can take as long as 1-2 days. Furthermore, non-professional users lack hardware and system knowledge, making independent deployment difficult, and the error rate from manual operation exceeds 30%.

[0006] 2. Insufficient environment adaptability and poor cross-platform compatibility. Due to differences in hardware architecture (such as x86 servers and ARM servers) and operating system versions (such as CentOS 7 and Ubuntu 22.04), installation packages need to be customized. However, traditional solutions lack automated environment awareness and version matching mechanisms, often leading to deployment failures due to dependency library version conflicts (such as GCC version incompatibility) or hardware architecture incompatibility. The cross-platform deployment success rate is only 60%-70%, which is insufficient to meet the rapid adaptation needs of multi-cloud environments and domestic hardware (such as Zhaoxin and Kunpeng).

[0007] 3. Dispersed privacy configurations pose significant security risks. Database deployment involves sensitive information such as administrator passwords, encryption certificates, and network access whitelists. In traditional solutions, these privacy parameters are often hard-coded in plaintext in scripts or configured in a dispersed manner through non-standardized interfaces, lacking a unified security verification and auditing mechanism, which can easily lead to the leakage of sensitive information or uncontrolled configuration risks.

[0008] 4. High complexity in cluster deployment and difficulty in ensuring context consistency. In distributed database cluster scenarios, the configuration information of each node (such as IP address, port number, and storage path) relies on manual maintenance, which easily leads to context inconsistency issues (e.g., a node missing a firewall rule, causing cluster communication interruption). Traditional solutions lack unified management capabilities for environmental information such as hardware resources, network topology, and data models. Cluster initialization and troubleshooting require manual verification of each node, which is not only inefficient but also reduces system reliability due to human error.

[0009] III. Limitations of Existing Automation Solutions

[0010] Existing technologies improve deployment efficiency through script automation (Shell / Python), containerization (Docker), or orchestration tools (Kubernetes), but they have significant shortcomings in practical applications.

[0011] Script-based solutions rely on pre-written fixed scripts. When the deployment environment changes (such as adjusting configuration parameters or updating dependency versions), the script code needs to be modified frequently. This not only results in high maintenance costs but also makes it difficult to adapt to complex and ever-changing scenarios, with extremely poor flexibility.

[0012] Containerization solutions: Although they can isolate applications from their environment through images, the image building process still requires manual configuration of dependencies (such as library files and system tools), and they are highly dependent on the host machine's kernel version and hardware resources (such as CPU architecture and memory capacity), which can easily lead to deployment failures due to environmental differences.

[0013] Orchestration tools: They focus on resource scheduling and service management during cluster runtime, but have weak support for key pre-deployment steps (such as environment compatibility testing, installation package version matching, and permission pre-verification). They often require secondary development in conjunction with other tools and cannot form a complete automated closed loop of "environment awareness-decision-execution", resulting in a fragmented deployment process. Summary of the Invention

[0014] This invention addresses the problems in traditional automated database deployment, such as high requirements for user expertise, inefficient machine information perception, frequent manual intervention, and cumbersome privacy configuration, by providing a database installation and deployment method based on the MCP protocol.

[0015] The present invention provides a database installation and deployment method based on the MCP protocol, and the technical solution adopted to solve the above-mentioned technical problems is as follows:

[0016] A database installation and deployment method based on the MCP protocol includes the following steps:

[0017] S1. Based on the MCP protocol, standardized configuration of privacy information is implemented, and users can complete the relevant settings of privacy information through the operation interface;

[0018] S2. Leveraging the natural language parsing capabilities of the MCP protocol, receive user-input natural language deployment commands and trigger the deployment process: The MCP Server acts as the core processing hub, calling MCP Tools to collect full environmental information of the server, matching the appropriate installation package version, and determining whether the installation package needs to be transmitted online based on the server network status, and completing the scheduling of the installation package.

[0019] S3. Based on the selected installation package, detect the dependencies of the target environment and automatically install any missing software packages; then automatically perform database installation, initialization configuration, and monitoring component deployment.

[0020] S4. The MCP Server summarizes the status information of the entire process and returns the deployment results.

[0021] Optionally, the MCP Tools involved are lightweight cross-platform tool components that automatically collect full environmental information from the server.

[0022] As the decision-making center, MCP Server standardizes the privacy information configuration format based on the MCP protocol, parses user commands through a natural language interaction interface, and automatically triggers the database installation and deployment process.

[0023] Meanwhile, by defining a unified environment model through the MCP protocol, the context parameters of hardware, software, and security policies are standardized, enabling the MCP Server to dynamically adjust deployment strategies based on real-time environment information and achieve seamless cross-platform environment adaptation.

[0024] Optionally, in step S1, the user enters the privacy information of the database deployment in a standardized format configured by the MCP protocol through a preset page or API, including server login credentials, administrator account password, data encryption certificate and key, network access whitelist, and data storage path and permissions.

[0025] The privacy information entered by users through preset pages or APIs will serve as the core basis for security authentication, data encryption, and access control during subsequent deployment, ensuring that the deployment process meets privacy protection and access management requirements, while also providing MCPServer with the basic parameters for executing security policies.

[0026] Alternatively, when performing step S2, the user can input deployment requirements in natural language based on a preset page or API.

[0027] MCP Server calls the parsing rules in the suggestion dictionary and uses a natural language engine to extract key elements: database type, version, deployment mode, and target environment;

[0028] Subsequently, the MCP Server retrieves the deployment strategy template for the corresponding environment from the knowledge base, combines it with the security parameters in the privacy information configuration, and generates a standardized deployment work order that includes execution steps, resource requirements, and security constraints, thus transforming the user's natural language requirements into automated tasks.

[0029] Preferably, the prompt word library stores a set of natural language instructions and deployment task mapping rules, which are used by the MCP Server's natural language parsing engine to identify user intent and generate corresponding deployment work orders;

[0030] The knowledge base contains the environment model, dependencies, and deployment strategies required for database deployment, which are important bases for MCPServer's decision-making.

[0031] Optionally, in step S2, the MCP Server, acting as the core processing hub, calls MCP Tools to collect full environmental information from the server and match it to obtain a compatible installation package version, specifically including:

[0032] After translating the user's natural language requirements into automated tasks, the MCP Server distributes the lightweight tool MCP Tools to the target server, triggering the collection of full environmental information, including: hardware aspects such as CPU architecture, memory capacity, storage type and capacity; software aspects such as operating system version, kernel parameters and installed software; and network aspects such as IP address, available ports, firewall rules and network bandwidth.

[0033] After data collection is complete, the MCP Server compares the information with the environment model in the knowledge base and automatically selects suitable installation packages and deployment parameters to ensure that subsequent deployments are compatible with the hardware and software characteristics of the target environment.

[0034] Further optionally, step S3 specifically includes:

[0035] S3.1 Based on the selected installation package, the MCP Server first checks if the local cache exists. If it does, it calls the cache directly. If it needs to be obtained online, it downloads the package from the specified source as needed, based on the network bandwidth parameters and package size in the environment model. The database configuration file is automatically generated based on the environment information and the configuration template in the knowledge base.

[0036] S3.2 For distributed clusters, automatically start the services of each node, allocate replica roles according to the node hardware performance, complete cluster handshake and data synchronization through internal communication protocols, activate the database service, and create initial accounts and permissions based on the administrator information in the privacy configuration to complete the deployment and activation of the core database functions.

[0037] S3.3 After the database is deployed, real-time monitoring and operation and maintenance support for the database's running status can be achieved through probe distribution, indicator collection, alarm policy configuration and visualization.

[0038] Further optionally, step S3.3 specifically includes:

[0039] S3.3.1, MCP Server automatically distributes monitoring probes to the target server, and the probes collect key operational indicators in real time: resource utilization, database performance indicators and cluster status;

[0040] S3.3.2 Configuring the alarm threshold and notification method of the probe according to the alarm strategy of the environment model in the knowledge base;

[0041] S3.3.3 Integrate probe data into the visualization monitoring platform to generate a real-time dashboard that intuitively displays the database's operating status, providing data support for subsequent operation and maintenance.

[0042] Further optionally, step S4 specifically includes:

[0043] S4.1 The MCP Server uses log collection tools to summarize the execution data of the aforementioned steps, including timeline, environment information summary, configuration parameter details, human interaction records and execution results;

[0044] S4.2 Generate a structured deployment report based on the aggregated data and provide feedback through the user-specified channel. The deployment report includes the final status of the deployment results and detailed logs of each stage, marking the closed loop of the entire process from "user request" to "deployment completion", and providing data basis for subsequent optimization of deployment strategies.

[0045] Optionally, a smart decision-making assistance AI module is preset. This module integrates a historical fault handling knowledge base, process node execution rules, and environmental parameter analysis models to provide automated decision support during the intervention process.

[0046] During the execution of steps S1-S4, if critical points or unexpected bottlenecks are encountered, three levels of manual intervention are supported. The specific intervention process is as follows:

[0047] (1) During the execution of each node in the installation and deployment process, the node's running status is monitored in real time. If the current node fails to execute or times out, a first-level intervention is triggered immediately. If no abnormality is detected, the process automatically proceeds to the next node.

[0048] (2) For transient issues such as network fluctuations or file lock conflicts that can be recovered through retries, the first-level intervention automatically invokes the AI ​​retry mechanism driven by the intelligent decision-making assistance AI module to re-execute the current node operation according to preset rules:

[0049] (2a) If the retry is successful, record the AI ​​retry log, including the failed node ID, the time of the first failure, the number of retries and the recovery time, and the process is seamlessly connected to the next node;

[0050] (2b) If the attempt fails after retrying the number of times set in the preset rules, a secondary intervention is triggered;

[0051] (3) In cases where the AI ​​retry mechanism fails and a matching solution exists in the knowledge base, the secondary intervention calls on the user to intervene in the retry mechanism. The intelligent decision-making assistance AI module generates an option containing "checkpoint type + environment information + up to 3 recommended operations" and pushes the option information to the user. After the user selects an operation, they manually initiate a retry:

[0052] (3a) If the retry is successful, record the user intervention log, which includes the user operation content and the retry result, and the process continues to execute the next node;

[0053] (3b) If the retry fails, a level 3 intervention is triggered;

[0054] (4) In cases where user intervention fails or no solution exists in the knowledge base, the three-level intervention mechanism invokes the expert handling mechanism. The MCP Server pushes the complete fault information of the current node to the industry expert, who then investigates the root cause, performs the repair, and initiates a retry.

[0055] (4a) If the retry is successful, the expert processing log is recorded, including the root cause of the failure, the solution and the execution result, and the process continues to the next node;

[0056] (4b) If the retry fails, the final failure status is recorded, a work order containing complete fault information is automatically generated and submitted to the operation and maintenance management system, and the current deployment process is terminated.

[0057] The database installation and deployment method based on the MCP protocol of the present invention has the following advantages compared with the prior art:

[0058] 1. This invention uses MCP Server as its core and achieves full-process automation through the MCP protocol and MCP Tools. It lowers the user threshold by relying on natural language interaction and simplified configuration, enabling non-professional users to independently complete deployment. Through automated perception, decision-making, and execution, it improves the accuracy of machine information acquisition by over 90%, reduces manual intervention by 80%, and significantly improves deployment efficiency and versatility. It is suitable for the rapid and easy-to-use deployment of databases in multiple scenarios. It solves the problems of high user expertise requirements, inefficient machine information perception, frequent manual intervention, and cumbersome privacy configuration in traditional automated database deployment.

[0059] 2. This invention relies on the MCP Server driver, greatly reducing manual operation steps. Operators only need to input privacy information and trigger commands to complete the process, completely eliminating tedious operations such as manual configuration and dependency checking. Through natural language interaction, users do not need to have knowledge of operating systems and databases, and even non-operations professionals can achieve independent deployment. For users, the system automatically shields differences in hardware architecture and operating systems, achieving "foolproof" environment adaptation and greatly lowering the technical threshold. Database providers do not need to write customized scripts for different hardware and software environments; they only need to maintain a standardized knowledge base and prompt dictionary, as well as the general MCP Server tool, to quickly adapt to new scenarios.

[0060] 3. This invention achieves real-time perception and hierarchical handling of deployment anomalies by pre-setting judgment nodes in key stages such as environment detection, dependency re-installation, and configuration verification: it triggers a built-in retry mechanism for known problems; it generates structured interactive requests for complex problems, including environmental context information and recommended solutions, enabling non-professional users to make correct decisions; and it supports resuming the process from the current node after manual processing, avoiding repeated operations. Attached Figure Description

[0061] Appendix Figure 1 This is a flowchart of a method according to an embodiment of the present invention;

[0062] Appendix Figure 2 This is a flowchart of the three-level manual intervention process according to an embodiment of the present invention. Detailed Implementation

[0063] To make the technical solution, the technical problem solved, and the technical effect of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with specific embodiments.

[0064] The technical terms used in the following embodiments will now be explained.

[0065] MCP (Model Context Protocol) is a standardized protocol used to uniformly model, transmit, and parse context information such as hardware environment, software dependencies, and security policies during database deployment.

[0066] MCP Server: A central control component based on the MCP protocol. As the decision-making hub of the deployment process, it is responsible for receiving user instructions, scheduling MCP Tools to perform environment checks, coordinating deployment tasks, and returning results.

[0067] MCP Tools: A lightweight, cross-platform toolset invoked by the MCP Server to collect hardware information (CPU architecture, memory / hard disk capacity), operating system (kernel version, installed software), and network status of the target server, providing data support for deployment decisions.

[0068] Natural language instructions: Deployment requirements expressed by users in everyday language (such as "install a MySQL 8.0 cluster on the test server") are transformed into executable deployment tasks by the MCP Server's natural language parsing engine.

[0069] Cross-platform compatibility: The ability of a system to run normally under different hardware architectures (such as x86, ARM), operating systems (such as Linux, Windows), and deployment forms (physical machines, virtual machines, cloud servers).

[0070] Database deployment: The complete process of bringing database software from an installation package to a running state, including steps such as environment preparation, software installation, parameter configuration, service startup, and cluster initialization.

[0071] Dependency completion: Before database deployment, based on a specific method, automatically detects the missing necessary software components (such as OpenSSL, Python runtime) in the target environment and obtains compatible versions from the software source for installation.

[0072] Example: See attached document Figure 1 This embodiment proposes a database installation and deployment method based on the MCP protocol, which includes the following steps:

[0073] S1. Based on the MCP protocol, standardized configuration of privacy information is implemented, and users can complete the relevant settings of privacy information through the operation interface.

[0074] When performing step S1, the user enters the privacy information deployed in the database in a standardized format configured by the MCP protocol through a preset page or API. This includes server login credentials (IP, port and SSH key), administrator account password, data encryption certificate and key, network access whitelist (restricting the range of allowed IPs), and data storage path and permissions (such as read and write permissions and user group configuration).

[0075] The privacy information entered by users through preset pages or APIs will serve as the core basis for security authentication, data encryption, and access control during subsequent deployment, ensuring that the deployment process meets privacy protection and access management requirements, while also providing MCPServer with the basic parameters for executing security policies.

[0076] S2. Leveraging the natural language parsing capabilities of the MCP protocol, receive user-input natural language deployment commands and trigger the deployment process: The MCP Server acts as the core processing hub, calling MCP Tools to collect full environmental information of the server, matching the appropriate installation package version, and determining whether the installation package needs to be transmitted online based on the server network status, and completing the scheduling of the installation package.

[0077] When performing step S2, based on a preset page or API, the user enters the deployment requirements in natural language (such as "Deploy a PostgreSQL 14 master-slave cluster in a production environment").

[0078] The MCP Server calls the parsing rules in the prompt word library and uses the natural language engine to decompose the key elements: database type (PostgreSQL), version (14), deployment mode (master-slave cluster) and target environment (production environment); among them, the prompt word library stores a set of natural language instructions and deployment task mapping rules, which are used by the MCP Server's natural language parsing engine to identify user intent and generate corresponding deployment work orders;

[0079] Subsequently, the MCP Server retrieves the deployment strategy template for the corresponding environment from the knowledge base (such as the high availability configuration and backup strategy required for the production environment), and combines it with the security parameters in the privacy information configuration to generate a standardized deployment work order containing execution steps, resource requirements, and security constraints, thus transforming the user's natural language requirements into automated tasks. The knowledge base, which stores the environment model, dependencies, and deployment strategies required for database deployment, is a crucial basis for the MCP Server's decision-making.

[0080] In step S2, the MCP Server, acting as the core processing hub, calls MCP Tools to collect full environmental information from the server and matches it to obtain a compatible installation package version, specifically including:

[0081] After translating the user's natural language requirements into automated tasks, the MCP Server distributes the lightweight tool MCP Tools to the target server, triggering a full collection of environmental information. This includes: hardware aspects such as CPU architecture (x86 / ARM), memory capacity (e.g., 16GB), storage type (SSD / HDD), and capacity; software aspects such as operating system version (e.g., CentOS 7.9), kernel parameters (e.g., memory page size), and installed software (to avoid version conflicts); and network aspects such as IP address, available ports (e.g., whether port 3306 is in use), firewall rules (whether database port communication is allowed), and network bandwidth (to assess the installation package transmission speed).

[0082] After data collection is complete, the MCP Server compares the information with the environment model in the knowledge base (such as "ARM architecture compatible version list" and "CentOS 7 compatible deployment parameters"), and automatically selects compatible installation packages (such as ARM architecture-specific MySQL installation packages) and deployment parameters (such as adjusting cache configuration according to memory size) to ensure that subsequent deployments are compatible with the hardware and software characteristics of the target environment.

[0083] S3. Based on the selected installation package, detect the dependencies of the target environment and automatically install any missing software packages; then automatically perform database installation, initialization configuration, and deployment of monitoring components.

[0084] This process specifically includes:

[0085] S3.1 Based on the selected installation package, MCP Server first checks if the local cache exists. If it does, it calls the cache directly. If it needs to be obtained online, it downloads the package from the specified source (such as the official mirror site and the enterprise's private repository) as needed, based on the network bandwidth parameters in the environment model and the size of the installation package. Based on the environment information (such as memory capacity and CPU core count) and the configuration template in the knowledge base, it automatically generates the database configuration file (such as my.cnf for MySQL, which includes cache size, connection limit, and log path, etc.).

[0086] S3.2 For distributed clusters (such as MySQL InnoDB Cluster), automatically start the services of each node, allocate replica roles (master node / slave node) according to the node hardware performance, complete cluster handshake and data synchronization through internal communication protocol, activate database services, and create initial accounts and permissions based on the administrator information in the privacy configuration (such as granting remote access permissions to the root user), and complete the deployment and activation of the core functions of the database.

[0087] S3.3 After the database deployment is completed, real-time monitoring and operation and maintenance support of the database's running status are achieved through probe distribution, indicator collection, alarm policy configuration, and visualization. The specific operations are as follows:

[0088] S3.3.1, MCP Server automatically distributes monitoring probes (such as Prometheus exporter) to the target server. The probes collect key operating indicators in real time: resource utilization (CPU, memory and disk I / O), database performance indicators (QPS, TPS, number of connections and number of slow queries) and cluster status (master-slave synchronization latency and node health).

[0089] S3.3.2. Based on the alarm strategy of the environment model in the knowledge base (such as "trigger an emergency alarm when the production environment memory usage rate is >90%" or "trigger a warning when the slave database synchronization delay is >30s"), configure the alarm threshold and notification method of the probe (such as email, SMS and monitoring platform interface).

[0090] S3.3.3 Connect the probe data to a visualization monitoring platform (such as Grafana) to generate a real-time dashboard that intuitively displays the database's operating status and provides data support for subsequent operation and maintenance.

[0091] S4. The MCP Server summarizes the status information of the entire process described above and returns the deployment results, specifically including:

[0092] S4.1 The MCP Server uses log collection tools to summarize the execution data of the aforementioned steps, including timelines (such as "dependency detection took 2 minutes" or "cluster initialization took 5 minutes"), environment information summary (hardware configuration and operating system version), configuration parameter details (such as key items in the configuration file), human interaction records (if there was temporary intervention), and execution results (success / failure and reason).

[0093] S4.2 Generate a structured deployment report based on the aggregated data and provide feedback through user-specified channels (such as web pages, emails, and API callbacks). The deployment report includes the final status of the deployment results and detailed logs of each stage (for easy problem tracing), marking the closed loop of the entire process from "user request" to "deployment completion", and providing data basis for subsequent optimization of deployment strategies.

[0094] It should be added that MCP Tools, as a lightweight cross-platform tool component, automatically collects full environmental information of the server, including hardware information (CPU architecture, memory / storage capacity), operating system fingerprint (kernel version, list of installed software) and network status;

[0095] As the decision-making center, MCP Server standardizes the privacy information configuration format based on the MCP protocol and parses user commands (such as "install MySQL cluster on server 192.168.123.101") through a natural language interaction interface, automatically triggering the database installation and deployment process;

[0096] Meanwhile, by defining a unified environment model through the MCP protocol, the context parameters of hardware, software and security policies are standardized, enabling the MCP Server to dynamically adjust deployment strategies based on real-time environment information (such as skipping the installation of high memory-consuming modules when memory is less than 8GB, and loading the corresponding version installation package when ARM architecture is detected), thus achieving seamless cross-platform environment adaptation.

[0097] Based on the deployment method of the embodiment, it should be further explained that an intelligent decision-making assistance AI module is preset. This module integrates a historical fault handling knowledge base, process node execution rules and environmental parameter analysis models to provide automated decision support during the intervention process.

[0098] During the execution of steps S1-S4, if critical points or unexpected bottlenecks are encountered, three levels of manual intervention are supported. (See attached document for details.) Figure 2 The specific intervention process is as follows:

[0099] (1) During the execution of each node in the installation and deployment process, the node's running status is monitored in real time. If the current node fails to execute or times out, a first-level intervention is triggered immediately. If no abnormality is detected, the process automatically proceeds to the next node.

[0100] (2) For transient issues such as network fluctuations or file lock conflicts that can be recovered through retries, the first-level intervention automatically invokes the AI ​​retry mechanism to re-execute the current node operation according to the rule of "10-second interval, 3 times by default (the retry interval and number of times can be adjusted through the configuration file)":

[0101] (2a) If the retry is successful, record the AI ​​retry log (including the failed node ID, the time of the first failure, the number of retries and the recovery time, and the process is seamlessly connected to the next node;

[0102] (2b) If the attempt fails after 3 retries, a secondary intervention is triggered;

[0103] (3) In cases where the AI ​​retry mechanism fails and a matching solution exists in the knowledge base, a secondary intervention calls upon the user to intervene in the retry mechanism. The intelligent decision-making assistance AI module generates options including "stuck point type + environment information + 2-3 recommended operations" (e.g., "Port 3306 is occupied: ① Automatically switch to 3307, ② Manually specify port, ③ Terminate"), and pushes the option information to the user. After selecting an operation, the user manually initiates a retry.

[0104] (3a) If the retry is successful, record the user intervention log, which includes the user operation content and the retry result, and the process continues to execute the next node;

[0105] (3b) If the retry fails, a level 3 intervention is triggered;

[0106] (4) In cases where user intervention fails or no solution exists in the knowledge base, the three-level intervention invokes the expert handling mechanism. The MCP Server pushes complete fault information (full log, error stack, and system snapshot) of the current node to industry experts. After the experts investigate the root cause and perform repairs (such as driver adaptation and kernel parameter adjustment), they initiate a retry.

[0107] (4a) If the retry is successful, the expert processing log is recorded, including the root cause of the failure, the solution and the execution result, and the process continues to the next node;

[0108] (4b) If the retry fails, the final failure status is recorded, a work order containing complete fault information is automatically generated and submitted to the operation and maintenance management system, and the current deployment process is terminated.

[0109] The first, second, and third level interventions are executed sequentially, with the next level intervention only triggered if the current first-level intervention fails. The execution order of the first, second, and third level interventions follows the principle of "progressive step-by-step," forming a tiered fault handling chain of "automatic repair → user intervention → expert handling," ensuring that problems are resolved according to their severity.

[0110] In summary, the database installation and deployment method based on the MCP protocol of this invention, with the MCP Server as the core, achieves full-process automation through the MCP protocol and MCP Tools; it lowers the user threshold by relying on natural language interaction and simplified configuration, enabling non-professional users to independently complete database installation and deployment; and it solves the problems of high user professional knowledge requirements, inefficient machine information perception, frequent manual intervention, and cumbersome privacy configuration in traditional automated database deployment.

[0111] The above specific examples illustrate the principles and implementation methods of the present invention in detail. These embodiments are merely for the purpose of helping to understand the core technical content of the present invention. Based on the above specific embodiments of the present invention, any improvements and modifications made to the present invention by those skilled in the art without departing from the principles of the present invention should fall within the patent protection scope of the present invention.

Claims

1. A database installation and deployment method based on the MCP protocol, characterized in that, Includes the following steps: S1. Based on the MCP protocol, standardized configuration of privacy information is implemented, and users can complete the relevant settings of privacy information through the operation interface; S2. Based on a preset page or API, users input deployment requirements in natural language; leveraging the natural language parsing capabilities of the MCP protocol, the system receives the user's natural language deployment instructions and triggers the deployment process: As the core processing hub, MCP Server first calls the parsing rules in the prompt dictionary and uses the natural language engine to extract key elements: database type, version, deployment mode, and target environment. Then, the deployment strategy template for the corresponding environment is retrieved from the knowledge base, and combined with the security parameters in the privacy information configuration, a standardized deployment work order containing execution steps, resource requirements and security constraints is generated, transforming the user's natural language requirements into automated tasks. After translating the user's natural language requirements into automated tasks, the MCP Server distributes the lightweight tool MCP Tools to the target server, triggering the collection of full environmental information, including: hardware aspects such as CPU architecture, memory capacity, storage type and capacity; software aspects such as operating system version, kernel parameters and installed software; and network aspects such as IP address, available ports, firewall rules and network bandwidth. After the data collection is completed, the MCP Server compares the information with the environment model in the knowledge base, automatically selects the appropriate installation package and deployment parameters, and ensures that the subsequent deployment is compatible with the hardware and software characteristics of the target environment. At the same time, it combines the server network status to determine whether the installation package needs to be transmitted online and completes the scheduling of the installation package. S3. Based on the selected installation package, detect the dependencies of the target environment and automatically install any missing software packages; then automatically perform database installation, initialization configuration, and monitoring component deployment. S4. The MCP Server summarizes the status information of the entire process and returns the deployment results.

2. The database installation and deployment method based on the MCP protocol according to claim 1, characterized in that, The MCP Tools, as a lightweight cross-platform tool component, automatically collects all environmental information from the server. The MCP Server serves as the decision-making center, standardizes the privacy information configuration format based on the MCP protocol, parses user commands through a natural language interaction interface, and automatically triggers the database installation and deployment process. Meanwhile, by defining a unified environment model through the MCP protocol, the context parameters of hardware, software, and security policies are standardized, enabling the MCP Server to dynamically adjust deployment strategies based on real-time environment information and achieve seamless cross-platform environment adaptation.

3. The database installation and deployment method based on the MCP protocol according to claim 1, characterized in that, In step S1, the user enters the privacy information deployed in the database through a preset page or API in a standardized format configured by the MCP protocol, including server login credentials, administrator account password, data encryption certificate and key, network access whitelist, and data storage path and permissions. The privacy information entered by users through preset pages or APIs will serve as the core basis for security authentication, data encryption, and access control during subsequent deployment, ensuring that the deployment process meets privacy protection and access management requirements, while also providing the MCP Server with the basic parameters for enforcing security policies.

4. The database installation and deployment method based on the MCP protocol according to claim 1, characterized in that, The prompt word library stores a set of natural language instructions and deployment task mapping rules, which are used by the MCP Server's natural language parsing engine to identify user intent and generate corresponding deployment work orders; The knowledge base stores the environment model, dependencies, and deployment strategies required for database deployment, and serves as an important basis for MCP Server decisions.

5. A database installation and deployment method based on the MCP protocol according to claim 1, characterized in that, Step S3 specifically includes: S3.1 Based on the selected installation package, the MCP Server first checks if the local cache exists. If it does, it calls the cache directly. If it needs to be obtained online, it downloads the package from the specified source as needed, based on the network bandwidth parameters and package size in the environment model. The database configuration file is automatically generated based on the environment information and the configuration template in the knowledge base. S3.2 For distributed clusters, automatically start the services of each node, allocate replica roles according to the node hardware performance, complete cluster handshake and data synchronization through internal communication protocols, activate the database service, and create initial accounts and permissions based on the administrator information in the privacy configuration to complete the deployment and activation of the core database functions. S3.3 After the database is deployed, real-time monitoring and operation and maintenance support for the database's running status can be achieved through probe distribution, indicator collection, alarm policy configuration and visualization.

6. A database installation and deployment method based on the MCP protocol according to claim 5, characterized in that, Step S3.3 specifically includes: S3.3.1, MCP Server automatically distributes monitoring probes to the target server, and the probes collect key operational indicators in real time: resource utilization, database performance indicators and cluster status; S3.3.2 Configuring the alarm threshold and notification method of the probe according to the alarm strategy of the environment model in the knowledge base; S3.3.3 Integrate probe data into the visualization monitoring platform to generate a real-time dashboard that intuitively displays the database's operating status, providing data support for subsequent operation and maintenance.

7. A database installation and deployment method based on the MCP protocol according to claim 5, characterized in that, Step S4 specifically includes: S4.1 The MCP Server uses log collection tools to summarize the execution data of the aforementioned steps, including timeline, environment information summary, configuration parameter details, human interaction records and execution results; S4.2 Generate a structured deployment report based on the aggregated data and provide feedback through the user-specified channel. The deployment report includes the final status of the deployment results and detailed logs of each stage, marking the closed loop of the entire process from "user request" to "deployment completion", and providing data basis for subsequent optimization of deployment strategies.

8. A database installation and deployment method based on the MCP protocol according to claim 1, characterized in that, A smart decision-making support AI module is pre-set. This module integrates a historical fault handling knowledge base, process node execution rules, and environmental parameter analysis models to provide automated decision support during intervention. During the execution of steps S1-S4, if critical points or unexpected bottlenecks are encountered, three levels of manual intervention are supported. The specific intervention process is as follows: (1) During the execution of each node in the installation and deployment process, the node's running status is monitored in real time. If the current node fails to execute or times out, a first-level intervention is triggered immediately. If no abnormality is detected, the process automatically proceeds to the next node. (2) For transient issues such as network fluctuations or file lock conflicts that can be recovered through retries, the first-level intervention automatically invokes the AI ​​retry mechanism driven by the intelligent decision-making assistance AI module to re-execute the current node operation according to preset rules: (2a) If the retry is successful, record the AI ​​retry log, including the failed node ID, the time of the first failure, the number of retries and the recovery time, and the process is seamlessly connected to the next node; (2b) If the attempt fails after retrying the number of times set in the preset rules, a secondary intervention is triggered; (3) In cases where the AI ​​retry mechanism fails but a matching solution exists in the knowledge base, the secondary intervention calls the user-intervention retry mechanism. The intelligent decision-making assistance AI module generates an option containing "checkpoint type + environment information + up to 3 recommended operations" and pushes the option information to the user. After the user selects an operation, they manually initiate a retry: (3a) If the retry is successful, record the user intervention log, which includes the user operation content and the retry result, and the process continues to execute the next node; (3b) If the retry fails, a level 3 intervention is triggered; (4) In cases where user intervention fails or no solution exists in the knowledge base, the three-level intervention mechanism invokes the expert handling mechanism. The MCP Server pushes the complete fault information of the current node to the industry expert, who then investigates the root cause, performs the repair, and initiates a retry. (4a) If the retry is successful, the expert processing log is recorded, including the root cause of the failure, the solution and the execution result, and the process continues to the next node; (4b) If the retry fails, the final failure status is recorded, a work order containing complete fault information is automatically generated and submitted to the operation and maintenance management system, and the current deployment process is terminated.

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